Figure 1: Map

See stationmap.R (lots of packages there’s no need to call for the other figures).

Figure 2: Conceptual diagram

For this I use the package DiagrammR, intending to show how the different data types flow into each other for assessment.

## Linking to librsvg 2.57.0

##Figure 2: map The bathymetry file is too large to include in this repo, and the mapping packages are somewhat specific, but let me know if you’d like it and I will send you the relevant files and code!

Figure 3: Eukaryotic time series

Figure 3 represents combined time series of Alexandrium 18s, saxitoxin, Pseudo-nitzschia 18s, domoic acid, and chl-a concentration, for general time series view of the data

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Figure 4: qPCR vs toxin

Figure 4 compares toxin concentration to qPCR counts/mL of matched peterson stations

## Estimating learning rate. Each dot corresponds to a loss evaluation. 
## qu = 0.75........done
## Estimating learning rate. Each dot corresponds to a loss evaluation. 
## qu = 0.9........done

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Figure 5: 18s vs toxin

Figure 5 compares toxin concentration to 18S of matched peterson stations. It proceeds to bootstrap 1000x, and extracts the 95th and 5th percentiles of at each chlorophyll value from the bootstrapped CPAs to represent the confidence interval

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Small version of plot for visual abstract

Figure 6: Version that combines all seasons and the chlorophyll histograms

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Broad-spectrum plot for visual abstract

Figure 7 (Combined CPA for all seasons, quantifying nonlinear increases in probability)

This section takes a subset of taxa from the previous plot and then creates a combined CPA, in this case looking at the likelihood of Dinophysis OR Alexandrium or Heterosigma exceeding their respective threshold relative abundances. I also include a couple methods of identifying inflections in the data: one is a changepoint analysis using the EnvCPT package, using a technique similar to ARIMA to identify inflections. The other is a GAM fit to the CPA data, then isolating the instantaneous change of the GAM function using a function called “derivatives” from the gratia package. It allows us to see what parts of the distribution are associated with greater change in likelihood.

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Figure S1: Metabarcoding validation

Figure S1 compares microscopy and qPCR values to the 18S data

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Figure S3: Seasonality of toxin concentration

Figure S3 shows how toxin concentrations vary by season

## # A tibble: 849 × 15
## # Groups:   Date, SiteCode2, toxin [849]
##    Date       Year  Month DOY        SiteCode2 Region  toxin value value2 detect
##    <date>     <chr> <ord> <date>     <chr>     <chr>   <chr> <dbl>  <dbl> <chr> 
##  1 2015-10-28 2015  Oct   1904-10-28 PSP       Centra… STX   -88      0   Non-d…
##  2 2015-10-28 2015  Oct   1904-10-28 LL        Centra… STX    11.5   11.5 Detec…
##  3 2015-10-28 2015  Oct   1904-10-28 RB        Centra… STX   -88      0   Non-d…
##  4 2015-10-28 2015  Oct   1904-10-28 RW        South … STX   -88      0   Non-d…
##  5 2015-10-28 2015  Oct   1904-10-28 OP        South … STX   -88      0   Non-d…
##  6 2015-10-28 2015  Oct   1904-10-28 CP        South … STX   -88      0   Non-d…
##  7 2015-10-28 2015  Oct   1904-10-28 TI        Centra… STX   -88      0   Non-d…
##  8 2015-10-28 2015  Oct   1904-10-28 BI        South … STX   -88      0   Non-d…
##  9 2015-10-28 2015  Oct   1904-10-28 EM        Centra… STX   -88      0   Non-d…
## 10 2015-12-14 2015  Dec   1904-12-14 TM        Centra… STX   -88      0   Non-d…
## # ℹ 839 more rows
## # ℹ 5 more variables: HighCount <chr>, Presence <chr>, Dayofyear <int>,
## #   Subembayment <chr>, NearestPeterson <chr>
## # A tibble: 849 × 15
## # Groups:   Date, SiteCode2, toxin [849]
##    Date       Year  Month DOY        SiteCode2 Region  toxin value value2 detect
##    <date>     <chr> <ord> <date>     <chr>     <chr>   <chr> <dbl>  <dbl> <chr> 
##  1 2015-10-28 2015  Oct   1904-10-28 PSP       Centra… STX   -88      0   Non-d…
##  2 2015-10-28 2015  Oct   1904-10-28 LL        Centra… STX    11.5   11.5 Detec…
##  3 2015-10-28 2015  Oct   1904-10-28 RB        Centra… STX   -88      0   Non-d…
##  4 2015-10-28 2015  Oct   1904-10-28 RW        South … STX   -88      0   Non-d…
##  5 2015-10-28 2015  Oct   1904-10-28 OP        South … STX   -88      0   Non-d…
##  6 2015-10-28 2015  Oct   1904-10-28 CP        South … STX   -88      0   Non-d…
##  7 2015-10-28 2015  Oct   1904-10-28 TI        Centra… STX   -88      0   Non-d…
##  8 2015-10-28 2015  Oct   1904-10-28 BI        South … STX   -88      0   Non-d…
##  9 2015-10-28 2015  Oct   1904-10-28 EM        Centra… STX   -88      0   Non-d…
## 10 2015-12-14 2015  Dec   1904-12-14 TM        Centra… STX   -88      0   Non-d…
## # ℹ 839 more rows
## # ℹ 5 more variables: HighCount <chr>, Presence <chr>, Dayofyear <int>,
## #   Subembayment <chr>, NearestPeterson <chr>
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Figure S4: Chl-a vs toxin concentration by season

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